The AI and Machine Learning Advances Journal works towards becoming a leading journal for AI/ ML research findings. In this way, it performs a function of connecting academic, industrial, top machine learning algorithms and governmental researchers to exchange know-how and innovations that are shaping the development of intelligent systems at the present time.
This review aims to examine the amount of ethical bias that is associated with the ambiguous aspect of the AI and particularly the robo-advisory services in wealth management. Since these platforms are gradually becoming involved in consumers’ financial decisions, it becomes important to interpret the possible bias such as algorithm, thinking, learning, and systemic bias to affect users and the outcomes of these platforms. Main ethical considerations discussed in the study are derived from the literature review which includes the main ethical issues connected with robo-advisors. Using the system ontology and postmodern epistemology, the study addresses the issue of multiple biases and their effects on specific demographic populations. In addition, it defines a set of measures to address those biases and pragmatic approaches enhance the ethical approaches in the AI design, regulation and the education of consumers. At the end of the study, the recommendations of how future studies can be done to improve the way artificial intelligence is implemented responsibly in financial services is provided.
Ethical AI, Algorithmic Bias, Robo-Advisory Services, Financial Inclusion, User Trust, Intersectionality.